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PROCESS SYSTEMS ENGINEERING Global Optimization of Mixed-Integer Nonlinear
 

Summary: PROCESS SYSTEMS ENGINEERING
Global Optimization of Mixed-Integer Nonlinear
Problems
C. S. Adjiman, I. P. Androulakis, and C. A. Floudas
Dept. of Chemical Engineering, Princeton University, Princeton, NJ 08544
Two no容l deterministic global optimization algorithms for noncon容x mixed-integer
( )problems MINLPs are proposed, using the ad家nces of the BB algorithm for non-
con容x NLPs of Adjiman et al. The special structure mixed-integer BB algorithm
( )SMIN- BB addresses problems with noncon容xities in the continuous 家riables and
linear and mixed-bilinear participation of the binary 家riables. The general structure
( )mixed-integer BB algorithm GMIN- BB is applicable to a 容ry general class of
problems for which the continuous relaxation is twice continuously differentiable. Both
algorithms are de容loped using the concepts of branch-and-bound, but they differ in
their approach to each of the required steps. The SMIN- BB algorithm is based on the
con容x underestimation of the continuous functions, while the GMIN- BB algorithm
is centered around the con容x relaxation of the entire problem. Both algorithms rely on
optimization or inter家l-based 家riable-bound updates to enhance efficiency. A series of
medium-size engineering applications demonstrates the performance of the algorithms.
Finally, a comparison of the two algorithms on the same problems highlights the 家lue
of algorithms that can handle binary or integer 家riables without reformulation.

  

Source: Androulakis, Ioannis (Yannis) - Biomedical Engineering Department & Department of Chemical and Biochemical Engineering, Rutgers University

 

Collections: Engineering; Biology and Medicine